A PILOT STUDY TO INCORPORATE REMOTELY OBTAINED BEDDING ATTITUDES INTO BEDROCK GEOLOGIC MAPPING PROJECTS IN VIRGINIA

Modern geologic mapping involves traditional fieldwork, remote sensing interpretation, and compilation of geologic data into standardized geodatabases and map products. The Virginia Department of Energy - Geology and Mineral Resources Program (GMR) has an active geologic mapping program employing the above approaches and incorporating readily available 1-meter resolution bare-earth LIDAR digital elevation models (DEMs) downloaded from the USGS 3D Elevation Program. Shaded relief (hillshade) and “slopeshade” rasters derived from these DEMs highlight geologic features with pronounced topographic signatures, particularly in heavily vegetated and difficult-to-access areas. In the Valley and Ridge Geologic Province of Virginia, a geologist familiar with the local stratigraphy can confidently trace bedding for considerable distances. Using a recently developed computer application, findSD, geologists can also remotely obtain strike and dip values by simply digitizing pronounced beds and utilizing findSD to compute the strike and dip. The data can then be added to the project geodatabase and incorporated into map products, with symbology or attribution indicating which bedding attitudes were collected using remote methods. There is no standardized symbology approved by the Federal Geographic Data Committee for structural data derived from LIDAR, however the development of such symbology is needed. The findSD tool has been field verified in a few locations with abundant outcrop. Over the next year, GMR geologists will test the accuracy of data obtained using this method in select locations within their project areas. While this process will not identify all outcrop-scale changes in bedding attitudes, it may provide attitudes that are more representative of the map-scale structure. This is especially useful at large outcrops with bedding that is variable or hard to discern. In addition, this tool will allow for the determination of an attitude in areas where bedding is visible on LIDAR DEMs and outcrop is not present. Field observations will continue to be important to better understand the characteristics of the bedrock, but this method can create a useful supplemental layer of data to fill in data gaps on mapping projects where field access is an issue.